The present invention relates to a fluid supply system with a pipeline network. More particularly, the invention is directed to a method for providing an optimum distribution of fluid to all the consumers by controlling the flow rate and the fluid pressure in the pipeline network on the basis of the prediction of demand at nodes of the network.
Although the present invention is equally applicable to various kinds of fluid supply systems such as a water supply system and a fuel gas supply system, its application to a water supply system will be described for ease of explanation. As is well known, a water supply system comprises a large scale pipeline network connecting all the consumers to a water supply source including reservoirs and purification plant units.
In FIG. 1 showing this kind of pipeline network, numeral 1 denotes a reservoir from which water is supplied to consumers by way of a pipeline 2. Numeral 3 represents a flow meter for measuring the flow rate of the water in the pipeline 2. N.sub.1, N.sub.2, N.sub.3 . . . N.sub.6 represent nodes of the main pipeline network, from which water is supplied by way of individual pipelines to consumers living in areas or districts D.sub.1, D.sub.2, D.sub.3 . . . D.sub.6, respectively.
For example, all the consumers n.sub.51, n.sub.52 . . . n.sub.5m living in the area D.sub.5 are supplied from the node N.sub.5 by way of individual pipelines. Each node of the network in this figure is hereinafter referred to as a demand node.
Numerals 4, 5, and 6 represent valves each provided for controlling the flow rate in the pipeline between appropriate demand nodes, and numeral 7 denotes a pump placed in the pipeline between the demand nodes N.sub.1 and N.sub.2 to control the water pressure thereof.
Furthermore, Q(t) represents the amount of water changing with time (t), which is supplied from the reservoir 1, and Q.sub.n1 (t), Q.sub.n2 (t), . . . Q.sub.n6 (t) represent the amounts of water demand changing with time (t) at nodes N.sub.1, N.sub.2 . . . N.sub.6 respectively.
In order to optimize the distribution of water to the consumers, it is necessary to control the flow rate and water pressure by regulating the pumps and valves in the pipeline network in accordance with the amount of water demand at all the nodes.
A problem in this system is, of course, how to predict, with high accuracy, the demand for water at each node. Where a flow meter is provided at each demand node of the network to measure the total amount of water being supplied from each node to the individual consumers, a considerably accurate prediction of future demands will be made from data measured in the past. However, since there are usually as many as 100 to 500 nodes in a large scale pipeline network, it is difficult from an economical viewpoint to provide a flow meter and associated equipment for telemetering data at each node.
Meanwhile, on the side of consumers, individual flow rate indicators are provided for use in calculating water rates or charges based upon indications of water consumption.
In the prior art, the demand for water at each node was predicted using information related to the amount of water consumption in the past at each node, which is obtained from the sum of indications of individual flow indicators and data on the flow rate Q(t) supplied from the reservoir 1.
However, even operators having much experience and skilled in this art often are faced with difficulties in controlling the distribution of water because of the shortage of data necessary for the prediction of water demand at the nodes.
Moreover, this prior art technique, relying largely on the experience of a skilled person is disadvantageous from time and cost saving viewpoints.
The amount of water consumption changes depending greatly upon the characteristics or attributes of the districts or areas to which water is to be distributed, such as whether the district is residential area or public office area. Since the prior art technique does not consider such characteristics or attributes of areas, it is difficult to predict with high accuracy the demand for water at each node.